Jelani Nelson, Assistant Professor of Computer Science and an expert in algorithms for big data analysis, has been selected to receive the prestigious NSF CAREER Award!
Students develop hurricane response plans on Cambridge roads, gaining practical experience in computational science
Imagine a powerful hurricane has wreaked havoc on the city of Cambridge, Mass. Thousands of residents are injured, but debris blocks roads everywhere, preventing medical workers from reaching the victims.
Crews are mobilizing to clear paths between the victims and two medical centers, Mount Auburn Hospital and Harvard University Health Services. Which roads should they open first, in order to quickly reach the largest number of victims? How many of those roads can they actually clear each day with the equipment available?
This was the problem posed to tech-savvy students participating in the IACS Computational Challenge in January. The competition was part of ComputeFest, a 2-week program hosted by the recently created Institute for Applied Computational Science (IACS) within the Harvard School of Engineering and Applied Sciences (SEAS).
“The amount of debris created by regularly occurring disasters is huge,” said Özlem Ergun, Visiting Associate Professor of Applied Mathematics at SEAS. In her usual post, Ergun is co-director of the Center for Health and Humanitarian Logistics at Georgia Institute of Technology, where she helps emergency management officials plan their response to disasters.
“The first problem,” she said, “is really to figure out in what order to open the streets so that you create connectivity between the population and the critical infrastructure.”
The Cambridge debris data was generated by Georgia Tech graduate students using the Federal Emergency Management Agency (FEMA) Hazus software, which visually models the human and environmental impacts of earthquakes, hurricanes, and floods.
In the Challenge scenario, 2,478 disaster victims were distributed unevenly across 443 Cambridge locations served by two hospitals (one large, one small), connected by 604 road segments (blocked by varying amounts of debris), and accessed via a fleet of bulldozers that roughly doubled in size over a 9-day cleanup period. A penalty was imposed to simulate the real-life pressure of time—the chance of people losing their lives if help took too long to arrive.
In short, the number of data points and constraints was huge…. [more]
Relationships uncovered in data from biology, baseball, and more
Cambridge, Mass. – December 16, 2011 – Researchers from the Broad Institute and Harvard University have developed a tool that can tackle large data sets in a way that no other software program can.
Part of a suite of statistical tools called MINE, it can tease out multiple patterns hidden in health information from around the globe, statistics amassed from a season of major league baseball, data on the changing bacterial landscape of the gut, and much more.
The researchers report their findings in a paper appearing today in the journal Science.
From Facebook to physics to the global economy, the world is filled with data sets that could take a person hundreds of years to analyze by eye. Sophisticated computer programs can search these data sets with great speed, but fall short when researchers attempt to even-handedly detect different kinds of patterns in large data collections…. [more]
Research in computer science addresses the tension between rapid technological progress and data privacy
Rachel Greenstadt ’07 (Ph.D.) is an Assistant Professor of Computer Science at Drexel University, where she runs the Privacy, Security, and Automation Laboratory. Her research group aims to develop autonomous systems that are trustworthy enough to handle sensitive data and important decisions.
Her interdisciplinary research currently involves the way machine learning technologies interact with security and privacy problems. In particular, she investigates whether algorithms can identify individuals by their linguistic writing style and whether individuals can, in turn, modify their style to evade such detection.
What problem interests you the most in the area of personal data privacy?
I am deeply interested in how the ease of storing, transferring, and analyzing electronic data changes the balance of power in our society, particularly the power between large organizations and individuals, but also our intimate social relationships. How we respond to these changes, both in terms of institutions and technologies, will affect what sort of society we become….
Chased by a helicopter, indoors
An energetic member of our Robobees engineering team demonstrates an impressive control algorithm that will eventually be used to help tiny robotic bees navigate an environment autonomously.
Luminaries from academia and industry will help usher in Rabin’s 80th birthday at a conference held August 29-30
On August 29-30, 2011, the Harvard School of Engineering and Applied Sciences (SEAS) will host a conference in celebration of computer scientist Michael Rabin’s 80th birthday.
Speakers will include Yonatan Aumann, Michael Ben-Or, Richard Karp, Dick Lipton, Silvio Micali, Michael Mitzenmacher, David Parkes, Tal Rabin, Ron Rivest, Dana Scott, Madhu Sudan, Salil Vadhan, Moshe Vardi, and Avi Wigderson.
Rabin is one of the most prominent computer scientists of the past 50 years. His contributions have influenced many foundational areas of the field….